Search results for: three dimensional data acquisition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26314

Search results for: three dimensional data acquisition

22354 Communication of Sensors in Clustering for Wireless Sensor Networks

Authors: Kashish Sareen, Jatinder Singh Bal

Abstract:

The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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22353 Democratic Political Culture of the 5th and 6th Graders under the Authority of Dusit District Office, Bangkok

Authors: Vilasinee Jintalikhitdee, Phusit Phukamchanoad, Sakapas Saengchai

Abstract:

This research aims to study the level of democratic political culture and the factors that affect the democratic political culture of 5th and 6th graders under the authority of Dusit District Office, Bangkok by using stratified sampling for probability sampling and using purposive sampling for non-probability sampling to collect data toward the distribution of questionnaires to 300 respondents. This covers all of the schools under the authority of Dusit District Office. The researcher analyzed the data by using descriptive statistics which include arithmetic mean, standard deviation, and inferential statistics which are Independent Samples T-test (T-test) and One-Way ANOVA (F-test). The researcher also collected data by interviewing the target groups, and then analyzed the data by the use of descriptive analysis. The result shows that 5th and 6th graders under the authority of Dusit District Office, Bangkok have exposed to democratic political culture at high level in overall. When considering each part, it found out that the part that has highest mean is “the constitutional democratic governmental system is suitable for Thailand” statement. The part with the lowest mean is “corruption (cheat and defraud) is normal in Thai society” statement. The factor that affects democratic political culture is grade levels, occupations of mothers, and attention in news and political movements.

Keywords: democratic, political culture, political movements, democratic governmental system

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22352 Optimizing the Performance of Thermoelectric for Cooling Computer Chips Using Different Types of Electrical Pulses

Authors: Saleh Alshehri

Abstract:

Thermoelectric technology is currently being used in many industrial applications for cooling, heating and generating electricity. This research mainly focuses on using thermoelectric to cool down high-speed computer chips at different operating conditions. A previously developed and validated three-dimensional model for optimizing and assessing the performance of cascaded thermoelectric and non-cascaded thermoelectric is used in this study to investigate the possibility of decreasing the hotspot temperature of computer chip. Additionally, a test assembly is built and tested at steady-state and transient conditions. The obtained optimum thermoelectric current at steady-state condition is used to conduct a number of pulsed tests (i.e. transient tests) with different shapes to cool the computer chips hotspots. The results of the steady-state tests showed that at hotspot heat rate of 15.58 W (5.97 W/cm2), using thermoelectric current of 4.5 A has resulted in decreasing the hotspot temperature at open circuit condition (89.3 °C) by 50.1 °C. Maximum and minimum hotspot temperatures have been affected by ON and OFF duration of the electrical current pulse. Maximum hotspot temperature was resulted by longer OFF pulse period. In addition, longer ON pulse period has generated the minimum hotspot temperature.

Keywords: thermoelectric generator, TEG, thermoelectric cooler, TEC, chip hotspots, electronic cooling

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22351 Saudi Human Awareness Needs: A Survey in How Human Causes Errors and Mistakes Leads to Leak Confidential Data with Proposed Solutions in Saudi Arabia

Authors: Amal Hussain Alkhaiwani, Ghadah Abdullah Almalki

Abstract:

Recently human errors have increasingly become a very high factor in security breaches that may affect confidential data, and most of the cyber data breaches are caused by human errors. With one individual mistake, the attacker will gain access to the entire network and bypass the implemented access controls without any immediate detection. Unaware employees will be vulnerable to any social engineering cyber-attacks. Providing security awareness to People is part of the company protection process; the cyber risks cannot be reduced by just implementing technology; the human awareness of security will significantly reduce the risks, which encourage changes in staff cyber-awareness. In this paper, we will focus on Human Awareness, human needs to continue the required security education level; we will review human errors and introduce a proposed solution to avoid the breach from occurring again. Recently Saudi Arabia faced many attacks with different methods of social engineering. As Saudi Arabia has become a target to many countries and individuals, we needed to initiate a defense mechanism that begins with awareness to keep our privacy and protect the confidential data against possible intended attacks.

Keywords: cybersecurity, human aspects, human errors, human mistakes, security awareness, Saudi Arabia, security program, security education, social engineering

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22350 A Method to Compute Efficient 3D Helicopters Flight Trajectories Based On a Motion Polymorph-Primitives Algorithm

Authors: Konstanca Nikolajevic, Nicolas Belanger, David Duvivier, Rabie Ben Atitallah, Abdelhakim Artiba

Abstract:

Finding the optimal 3D path of an aerial vehicle under flight mechanics constraints is a major challenge, especially when the algorithm has to produce real-time results in flight. Kinematics models and Pythagorian Hodograph curves have been widely used in mobile robotics to solve this problematic. The level of difficulty is mainly driven by the number of constraints to be saturated at the same time while minimizing the total length of the path. In this paper, we suggest a pragmatic algorithm capable of saturating at the same time most of dimensioning helicopter 3D trajectories’ constraints like: curvature, curvature derivative, torsion, torsion derivative, climb angle, climb angle derivative, positions. The trajectories generation algorithm is able to generate versatile complex 3D motion primitives feasible by a helicopter with parameterization of the curvature and the climb angle. An upper ”motion primitives’ concatenation” algorithm is presented based. In this article we introduce a new way of designing three-dimensional trajectories based on what we call the ”Dubins gliding symmetry conjecture”. This extremely performing algorithm will be soon integrated to a real-time decisional system dealing with inflight safety issues.

Keywords: robotics, aerial robots, motion primitives, helicopter

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22349 The Quality of Food and Drink Product Labels Translation from Indonesian into English

Authors: Rudi Hartono, Bambang Purwanto

Abstract:

The translation quality of food and drink labels from Indonesian into English is poor because the translation is not accurate, less natural, and difficult to read. The label translation can be found in some cans packages of food and drink products produced and marketed by several companies in Indonesia. If this problem is left unchecked, it will lead to a misunderstanding on the translation results and make consumers confused. This study was conducted to analyze the translation errors on food and drink products labels and formulate the solution for the better translation quality. The research design was the evaluation research with a holistic criticism approach. The data used were words, phrases, and sentences translated from Indonesian to English language printed on food and drink product labels. The data were processed by using Interactive Model Analysis that carried out three main steps: collecting, classifying, and verifying data. Furthermore, the data were analyzed by using content analysis to view the accuracy, naturalness, and readability of translation. The results showed that the translation quality of food and drink product labels from Indonesian to English has the level of accuracy (60%), level of naturalness (50%), and level readability (60%). This fact needs a help to create an effective strategy for translating food and drink product labels later.

Keywords: translation quality, food and drink product labels, a holistic criticism approach, interactive model, content analysis

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22348 Supervised Machine Learning Approach for Studying the Effect of Different Joint Sets on Stability of Mine Pit Slopes Under the Presence of Different External Factors

Authors: Sudhir Kumar Singh, Debashish Chakravarty

Abstract:

Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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22347 A Patent Trend Analysis for Hydrogen Based Ironmaking: Identifying the Technology’s Development Phase

Authors: Ebru Kaymaz, Aslı İlbay Hamamcı, Yakup Enes Garip, Samet Ay

Abstract:

The use of hydrogen as a fuel is important for decreasing carbon emissions. For the steel industry, reducing carbon emissions is one of the most important agendas of recent times globally. Because of the Paris Agreement requirements, European steel industry studies on green steel production. Although many literature reviews have analyzed this topic from technological and hydrogen based ironmaking, there are very few studies focused on patents of decarbonize parts of the steel industry. Hence, this study focus on technological progress of hydrogen based ironmaking and on understanding the main trends through patent data. All available patent data were collected from Questel Orbit. The trend analysis of more than 900 patent documents has been carried out by using Questel Orbit Intellixir to analyze a large number of data for scientific intelligence.

Keywords: hydrogen based ironmaking, DRI, direct reduction, carbon emission, steelmaking, patent analysis

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22346 3D Scanning Documentation and X-Ray Radiography Examination for Ancient Egyptian Canopic Jar

Authors: Abdelrahman Mohamed Abdelrahman

Abstract:

Canopic jars are one of the vessels of funerary nature used by the ancient Egyptian in mummification process that were used to save the viscera of the mummified body after being extracted from the body and treated. Canopic jars are made of several types of materials like Limestone, Alabaster, and Pottery. The studied canopic jar dates back to Late period, located in the Grand Egyptian Museum (GEM), Giza, Egypt. This jar carved from limestone with carved hieroglyphic inscriptions, and it filled and closed by mortar from inside. Some aspects of damage appeared in the jar, such as dust, dirts, classification, wide crack, weakness of limestone. In this study, we used documentation and investigation modern techniques to document and examine the jar. 3D scanning and X-ray Radiography imaging used in applied study. X-ray imaging showed that the mortar was placed at a time when the jar contained probably viscera where the mortar appeared that not reach up to the base of the inner jar. Through the three-dimensional photography, the jar was documented, and we have 3D model of the jar, and now we have the ability through the computer to see any part of the jar in all its details. After that, conservation procedures have been applied with high accuracy to conserve the jar, including mechanical, wet, and chemical cleaning, filling wide crack in the body of the jar using mortar consisting of calcium carbonate powder mixing with primal E330 S, and consolidation, so the limestone became strong after using paraloid B72 2% concentrate as a consolidate material.

Keywords: vessel, limestone, canopic jar, mortar, 3D scanning, X-ray radiography

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22345 The Effects of Electron Trapping by Electron-Ecoustic Waves Excited with Electron Beam

Authors: Abid Ali Abid

Abstract:

One-dimensional (1-D) particle-in-cell (PIC) electrostatic simulations are carried out to investigate the electrostatic waves, whose constituents are hot, cold and beam electrons in the background of motionless positive ions. In fact, the electrostatic modes excited are electron acoustic waves, beam driven waves as well as Langmuir waves. It is assessed that the relevant plasma parameters, for example, hot electron temperature, beam electron drift speed, and the electron beam density significantly modify the electrostatics wave's profiles. In the nonlinear stage, the wave-particle interaction becomes more evident and the waves have obtained its saturation level. Consequently, electrons become trapped in the waves and trapping vortices are clearly formed. Because of this trapping vortices and mixing of the electrons in phase space, finally, lead to electrons thermalization. It is observed that for the high-density value of the beam-electron, the solitary waves having a bipolar form of the electric field. These solitons are the nonlinear Brenstein-Greene and Kruskal wave mode that attributes the trapping of electrons potential well of phase-space hole. These examinations revealed that electrostatic waves have been exited in beam-plasma model and producing waves having broad-frequency ranges, which may clarify the broadband electrostatic noise (BEN) spectrum studied in the auroral zone.

Keywords: electron acoustic waves, trapping of cold electron, Langmuir waves, particle-in cell simulation

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22344 Fuzzy Logic Classification Approach for Exponential Data Set in Health Care System for Predication of Future Data

Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

Abstract:

Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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22343 Evaluation of Symptoms, Laboratory Findings, and Natural History of IgE Mediated Wheat Allergy

Authors: Soudeh Tabashi, Soudabeh Fazeli Dehkordy, Masood Movahedi, Nasrin Behniafard

Abstract:

Introduction: Food allergy has increased in three last decades. Since wheat is one of the major constituents of daily meal in many regions throughout the world, wheat allergy is one of the most important allergies ranking among the 8 most common types of food allergies. Our information about epidemiology and etiology of food allergies are limited. Therefore, in this study we sought to evaluate the symptoms and laboratory findings in children with wheat allergy. Materials and methods: There were 23 patients aged up to 18 with the diagnosis of IgE mediated wheat allergy that were included enrolled in this study. Using a questionnaire .we collected their information and organized them into 4 groups categories of: demographic data identification, signs and symptoms, comorbidities, and laboratory data. Then patients were followed up for 6 month and their lab data were compared together. Results: Most of the patients (82%) presented the symptoms of wheat allergy in the first year of their life. The skin and the respiratory system were the most commonly involved organs with an incidence of 86% and 78% respectively. Most of the patients with wheat allergy were also sensitive to the other type of foods and their sensitivity to egg were most common type (47%). in 57% of patients, IgE levels were decreased during the 6 month follow-up period. Conclusion: We do not have enough information about data on epidemiology and response to therapy of wheat allergy and to best of our knowledge no study has addressed this issue in Iran so far. This study is the first source of information about IgE mediated wheat allergy in Iran and It can provide an opening for future studies about wheat allergy and its treatments.

Keywords: wheat allergy, food allergy, IgE, food allergy

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22342 Thermodynamic Performance Tests for 3D Printed Steel Slag Powder Concrete Walls

Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

Abstract:

The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

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22341 Comparison between Some of Robust Regression Methods with OLS Method with Application

Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

Abstract:

The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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22340 Numerical Analysis of Shear Crack Propagation in a Concrete Beam without Transverse Reinforcement

Authors: G. A. Rombach, A. Faron

Abstract:

Crack formation and growth in reinforced concrete members are, in many cases, the cause of the collapse of technical structures. Such serious failures impair structural behavior and can also damage property and persons. An intensive investigation of the crack propagation is indispensable. Numerical methods are being developed to analyze crack growth in an element and to detect fracture failure at an early stage. For reinforced concrete components, however, further research and action are required in the analysis of shear cracks. This paper presents numerical simulations and continuum mechanical modeling of bending shear crack propagation in a three-dimensional reinforced concrete beam without transverse reinforcement. The analysis will provide a further understanding of crack growth and redistribution of inner forces in concrete members. As a numerical method to map discrete cracks, the extended finite element method (XFEM) is applied. The crack propagation is compared with the smeared crack approach using concrete damage plasticity. For validation, the crack patterns of real experiments are compared with the results of the different finite element models. The evaluation is based on single span beams under bending. With the analysis, it is possible to predict the fracture behavior of concrete members.

Keywords: concrete damage plasticity, crack propagation, extended finite element method, fracture mechanics

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22339 Uplifting Citizens Participation: A Gov 2.0 Framework

Authors: Mohammed Aladalah

Abstract:

The emergence of digital citizens is no longer mere speculation; therefore, governments’ use of Web 2.0 tools (hereafter Gov 2.0) should be a part of all current and future e-government plans. The potential of Gov 2.0 to facilitate greater communication, participation, and collaboration with citizens has been highlighted and discussed extensively in recent literature. However, the current levels of citizens’ participation in Gov 2.0 have not lived up to the hype. Therefore, governments need to rethink the way in which they implement Gov 2.0, and take advantage of the digitally-engaged population. We propose a two-dimensional framework to tackle this issue: first, on the supply side, governments tend to use Gov 2.0 mainly for the dissemination of information and for self-promotion without the desire to encourage any interaction with citizens; this is due to many reasons, including the lack of time and the possibility of loss of control. The second dimension of the framework is the demand side; citizens are unwilling to participate in Gov 2.0 activities because they do not perceive its value or trust the government. We attempt to consider the elements of both supply and demand in order to provide a comprehensive solution whereby the potential of Gov 2.0 can be fully utilized. Our framework is based on the theoretical foundation of service science and value co-creation theory. This paper makes two significant contributions: (a) it provides an initial framework intended to increase citizens’ participation in Gov 2.0; and (b) it enhances the understanding of the government’s Gov 2.0 applications, particularly in terms of factors that ensure their attractiveness for citizens. This work is the first step in a comprehensive research undertaking, the purpose of which is to study public’s engagement with the Gov 2.0 concept. It contributes to providing a better understanding of e-government and its future.

Keywords: e-government, Gov 2.0, citizens participation, digital citizen

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22338 Hybrid Fuzzy Weighted K-Nearest Neighbor to Predict Hospital Readmission for Diabetic Patients

Authors: Soha A. Bahanshal, Byung G. Kim

Abstract:

Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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22337 The Comparison of Joint Simulation and Estimation Methods for the Geometallurgical Modeling

Authors: Farzaneh Khorram

Abstract:

This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

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22336 Deriving Generic Transformation Matrices for Multi-Axis Milling Machine

Authors: Alan C. Lin, Tzu-Kuan Lin, Tsong Der Lin

Abstract:

This paper proposes a new method to find the equations of transformation matrix for the rotation angles of the two rotational axes and the coordinates of the three linear axes of an orthogonal multi-axis milling machine. This approach provides intuitive physical meanings for rotation angles of multi-axis machines, which can be used to evaluate the accuracy of the conversion from CL data to NC data.

Keywords: CAM, multi-axis milling machining, transformation matrix, rotation angles

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22335 A Stepwise Approach to Automate the Search for Optimal Parameters in Seasonal ARIMA Models

Authors: Manisha Mukherjee, Diptarka Saha

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Reliable forecasts of univariate time series data are often necessary for several contexts. ARIMA models are quite popular among practitioners in this regard. Hence, choosing correct parameter values for ARIMA is a challenging yet imperative task. Thus, a stepwise algorithm is introduced to provide automatic and robust estimates for parameters (p; d; q)(P; D; Q) used in seasonal ARIMA models. This process is focused on improvising the overall quality of the estimates, and it alleviates the problems induced due to the unidimensional nature of the methods that are currently used such as auto.arima. The fast and automated search of parameter space also ensures reliable estimates of the parameters that possess several desirable qualities, consequently, resulting in higher test accuracy especially in the cases of noisy data. After vigorous testing on real as well as simulated data, the algorithm doesn’t only perform better than current state-of-the-art methods, it also completely obviates the need for human intervention due to its automated nature.

Keywords: time series, ARIMA, auto.arima, ARIMA parameters, forecast, R function

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22334 Decision-Making Strategies on Smart Dairy Farms: A Review

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

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22333 Hydrothermal Energy Application Technology Using Dam Deep Water

Authors: Yooseo Pang, Jongwoong Choi, Yong Cho, Yongchae Jeong

Abstract:

Climate crisis, such as environmental problems related to energy supply, is getting emerged issues, so the use of renewable energy is essentially required to solve these problems, which are mainly managed by the Paris Agreement, the international treaty on climate change. The government of the Republic of Korea announced that the key long-term goal for a low-carbon strategy is “Carbon neutrality by 2050”. It is focused on the role of the internet data centers (IDC) in which large amounts of data, such as artificial intelligence (AI) and big data as an impact of the 4th industrial revolution, are managed. The demand for the cooling system market for IDC was about 9 billion US dollars in 2020, and 15.6% growth a year is expected in Korea. It is important to control the temperature in IDC with an efficient air conditioning system, so hydrothermal energy is one of the best options for saving energy in the cooling system. In order to save energy and optimize the operating conditions, it has been considered to apply ‘the dam deep water air conditioning system. Deep water at a specific level from the dam can supply constant water temperature year-round. It will be tested & analyzed the amount of energy saving with a pilot plant that has 100RT cooling capacity. Also, a target of this project is 1.2 PUE (Power Usage Effectiveness) which is the key parameter to check the efficiency of the cooling system.

Keywords: hydrothermal energy, HVAC, internet data center, free-cooling

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22332 A Comparative Asessment of Some Algorithms for Modeling and Forecasting Horizontal Displacement of Ialy Dam, Vietnam

Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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22331 COVID_ICU_BERT: A Fine-Tuned Language Model for COVID-19 Intensive Care Unit Clinical Notes

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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22330 Concept Analysis of Professionalism in Teachers and Faculty Members

Authors: Taiebe Shokri, Shahram Yazdani, Leila Afshar, Soleiman Ahmadi

Abstract:

Introduction: The importance of professionalism in higher education not only determines the appropriate and inappropriate behaviors and guides faculty members in the implementation of professional responsibilities, but also guarantees faculty members' adherence to professional principles and values, ensures the quality of teaching and facilitator will be the teaching-learning process in universities and will increase the commitment to meet the needs of students as well as the development of an ethical culture based on ethics. Therefore, considering the important role of medical education teachers to prepare teachers and students in the future, the need to determine the concept of professional teacher and teacher, and the characteristics of teacher professionalism, we have explained the concept of professionalism in teachers in this study. Methods: The concept analysis method used in this study was Walker and Avant method which has eight steps. Walker and Avant state the purpose of concept analysis as follows: The process of distinguishing between the defining features of a concept and its unrelated features. The process of concept analysis includes selecting a concept, determining the purpose of the analysis, identifying the uses of the concept, determining the defining features of the concept, identifying a model, identifying boundary and adversarial items, identifying the precedents and consequences of the concept, and defining empirical references. is. Results: Professionalism in its general sense, requires deep knowledge, insight, creating a healthy and safe environment, honesty and trust, impartiality, commitment to the profession and continuous improvement, punctuality, criticism, professional competence, responsibility, and Individual accountability, especially in social interactions, is an effort for continuous improvement, the acquisition of these characteristics is not easily possible and requires education, especially continuous learning. Professionalism is a set of values, behaviors, and relationships that underpin public trust in teachers.

Keywords: concept analysis, medical education, professionalism, faculty members

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22329 Development and Modeling of a Geographic Information System Solar Flux in Adrar, Algeria

Authors: D. Benatiallah, A. Benatiallah, K. Bouchouicha, A. Harouz

Abstract:

The development and operation of renewable energy known an important development in the world with significant growth potential. Estimate the solar radiation on terrestrial geographic locality is of extreme importance, firstly to choose the appropriate site where to place solar systems (solar power plants for electricity generation, for example) and also for the design and performance analysis of any system using solar energy. In addition, solar radiation measurements are limited to a few areas only in Algeria. Thus, we use theoretical approaches to assess the solar radiation on a given location. The Adrar region is one of the most favorable sites for solar energy use with a medium flow that exceeds 7 kWh / m2 / d and saddle of over 3500 hours per year. Our goal in this work focuses on the creation of a data bank for the given data in the energy field of the Adrar region for the period of the year and the month then the integration of these data into a geographic Information System (GIS) to estimate the solar flux on a location on the map.

Keywords: Adrar, flow, GIS, deposit potential

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22328 Mapping a Data Governance Framework to the Continuum of Care in the Active Assisted Living Context

Authors: Gaya Bin Noon, Thoko Hanjahanja-Phiri, Laura Xavier Fadrique, Plinio Pelegrini Morita, Hélène Vaillancourt, Jennifer Teague, Tania Donovska

Abstract:

Active Assisted Living (AAL) refers to systems designed to improve the quality of life, aid in independence, and create healthier lifestyles for care recipients. As the population ages, there is a pressing need for non-intrusive, continuous, adaptable, and reliable health monitoring tools to support aging in place. AAL has great potential to support these efforts with the wide variety of solutions currently available, but insufficient efforts have been made to address concerns arising from the integration of AAL into care. The purpose of this research was to (1) explore the integration of AAL technologies and data into the clinical pathway, and (2) map data access and governance for AAL technology in order to develop standards for use by policy-makers, technology manufacturers, and developers of smart communities for seniors. This was done through four successive research phases: (1) literature search to explore existing work in this area and identify lessons learned; (2) modeling of the continuum of care; (3) adapting a framework for data governance into the AAL context; and (4) interviews with stakeholders to explore the applicability of previous work. Opportunities for standards found in these research phases included a need for greater consistency in language and technology requirements, better role definition regarding who can access and who is responsible for taking action based on the gathered data, and understanding of the privacy-utility tradeoff inherent in using AAL technologies in care settings.

Keywords: active assisted living, aging in place, internet of things, standards

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22327 Remotely Sensed Data Fusion to Extract Vegetation Cover in the Cultural Park of Tassili, South of Algeria

Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

Abstract:

The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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22326 The Importance of Industrial Work Experience, Career Information, and Work Motivation to Increase Work Readiness

Authors: Nyaris Pambudiyatno, Asto Buditjahjanto, Eppy Yundra, Arie Wardhono, Eko Hariadi

Abstract:

Vocational education is part of the national education system that is prepared to produce graduates who have the skills and knowledge according to the needs and requirements required by the job. Vocational Education is a secondary education that prepares students to work in a particular field. The purpose of this study was to analyze and find out the effect of industrial work practice experience and career information on work readiness through work motivation. This type of research is causal research with a quantitative approach. The population in this study was 359 cadets of Aviation Polytechnic Surabaya. While the number of samples calculates using slovin calculations obtained by 189 cadets of Surabaya Aviation Polytechnic. The type of data used is quantitative data with the primary data source. Data collection techniques are by distributing questionnaires. Analysis of this study is with Lisrel. The findings prove that: (1) Industrial Work Experience experience has a positive and significant effect on work motivation; (2) Industrial Work Experience has a positive and significant impact on work readiness; (3) Career information has a positive and significant effect on job readiness; (4) Career information has a positive and significant impact on job readiness; Dan (5) Work motivation has a positive and significant effect on work readiness.

Keywords: career information, increase work readiness, industrial work experience, work motivation

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22325 Assessment of Pier Foundations for Onshore Wind Turbines in Non-cohesive Soil

Authors: Mauricio Terceros, Jann-Eike Saathoff, Martin Achmus

Abstract:

In non-cohesive soil, onshore wind turbines are often found on shallow foundations with a circular or octagonal shape. For the current generation of wind turbines, shallow foundations with very large breadths are required. The foundation support costs thus represent a considerable portion of the total construction costs. Therefore, an economic optimization of the type of foundation is highly desirable. A conceivable alternative foundation type would be a pier foundation, which combines the load transfer over the foundation area at the pier base with the transfer of horizontal loads over the shaft surface of the pier. The present study aims to evaluate the load-bearing behavior of a pier foundation based on comprehensive parametric studies. Thereby, three-dimensional numerical simulations of both pier and shallow foundations are developed. The evaluation of the results focuses on the rotational stiffnesses of the proposed soil-foundation systems. In the design, the initial rotational stiffness is decisive for consideration of natural frequencies, whereas the rotational secant stiffness for a maximum load is decisive for serviceability considerations. A systematic analysis of the results at different load levels shows that the application of the typical pier foundation is presumably limited to relatively small onshore wind turbines.

Keywords: onshore wind foundation, pier foundation, rotational stiffness of soil-foundation system, shallow foundation

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